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Article

Biodiversity of Diatoms as Indicators of Water Quality and Landscape Sustainable Dynamics in the Zarafshan River, Uzbekistan

by
Karomat Mamanazarova
1,
Kholiskhon Alimjanova
1 and
Sophia Barinova
2,*
1
Institute of Botany of Uzbek Academy of Sciences, Tashkent 100125, Uzbekistan
2
Institute of Evolution, University of Haifa, Abba Khoushi Ave, 199, Mount Carmel, Haifa 3498838, Israel
*
Author to whom correspondence should be addressed.
Land 2024, 13(11), 1809; https://doi.org/10.3390/land13111809
Submission received: 11 September 2024 / Revised: 29 October 2024 / Accepted: 30 October 2024 / Published: 1 November 2024
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Abstract

:
For the first time, we have compiled a general list of diatoms for the Zarafshan River consisting of 428 species based on our own research and the literature data. Indicator species for nine water parameters were identified, making up more than 90% of the list. Bioindicators and statistical methods revealed that sections of the river around the city of Samarkand and further in the middle reaches reflect the complexity of the impact of the environment on diatom communities. The surveyed sections of the middle reaches of the river are divided into branches and the dynamics of water parameters and diatom communities are shown from the border with Tajikistan to the confluence of the Zarafshan with the Amu Darya. The indices of organic pollution, S, and toxic impact, WESI, were calculated. They show that there is an increase in salinity and turbidity and a decrease in organic pollution downriver. At the same time, the Navoi section is a source of water acidification. Nutrients and heavy metals, as well as phenol pollution, enter the river from various sources, mainly in the middle reaches of the river. The Zarafshan Nature Reserve in the catchment area of the upper section of the river within Uzbekistan is important for maintaining water quality. Bioindicators show an increase in self-purification, with an increase in the species richness and abundance of diatoms in the middle section of the Zarafshan River. The integrated index of river pollution, RPI, shows that most pollution comes from the northern canal of the river in the middle reaches. A general look at the Zarafshan River catchment basin and the dynamics of the identified water parameters and bioindicator species of diatoms shows that the river ecosystem successfully copes with incoming pollution, including transboundary impacts from Tajikistan. Such a conclusion could not be made based on chemical analysis of the water alone. This allowed us to recommend expanding state monitoring points to the lower section of Karakul while including biological indicators in the observations.

1. Introduction

Of great importance in the life of aquatic organisms, including algae, is the nature of the trophic state, the altitude above sea level, the types of soil or rocks, and other factors that determine the degree of water transparency, its temperature, the quantity and qualitative composition of the salts dissolved in it, and some other ecological features that are vital for the aquatic ecosystems [1].
Much attention is paid in the world to monitoring the state of large aquatic ecosystems, assessing the level of transformation of biota under the influence of strong anthropogenic and technogenic influence. The main waterways of Central Asia are the Syr Darya, Amu Darya, Zarafshan, Chirchik, Talas, Chu, and Murgob, the waters of which have been used for irrigation of cultivated fields since time immemorial. For this purpose, various irrigation and drainage canals, reservoirs, etc., were created [1]. Thus, water resources in the semi-desert and desert climate zone are vital, supporting the existence and economy of the countries of the region. It should be noted that almost all mountain water bodies (including the Zarafshan River), are basically fed by snow. Rain plays an insignificant role in this regard [2]. However, this resource replenishes the river mainly in its upper reaches, outside of Uzbekistan. In transboundary rivers, water flows from different geographic regions and the widespread use of water resources in agriculture and other economic sectors lead to changes in aquatic organism communities [3].
Water quality is a critical variable in conditions of limited water resources [4]. For Uzbekistan, such a main waterway is the Zarafshan River. This is the only river flowing through the entire territory of the country, supporting its economy, population, economy, and biodiversity. The upper part of the river’s catchment area is located outside the country, so the river is transboundary [5].
In most cases, population growth in the areas of large rivers, an increase in the number of livestock, and wastewater discharge lead to radical changes in river algal flora and the formation of new species in the basin flora [6]. Excessive input of nutrients such as nitrogen and phosphorus into rivers can have significant impacts on benthic algal communities [7]. In mountain streams, diatoms are the most abundant and diverse taxonomic group in benthic algal communities [8].
Diatoms are increasingly used to assess short-term and long-term environmental changes because they are informative, versatile, flexible, and powerful environmental indicators, as they respond rapidly to changes in many environmental factors [9,10]. Thus, through having data on the diversity of diatoms in a river, one can discuss changes in water quality and sources of its pollution. Moreover, the experience of ecological mapping of chemical pollution parameters and toxicity indices, as was performed for the Arys River basin in the nearby region of Kazakhstan [11], opens up opportunities for linking data to the landscape and allows for the identification of critical areas in the river catchment basin.
An analysis of the literature data on the diversity of diatoms in the Zarafshan River showed that a generalized assessment of its ecological state in terms of algal diversity has not yet been carried out. However, some fragmentary data are known. In previous years, the hydrochemical indicators and composition of periphyton algae in the Zarafshan River were given separately for the upper, middle, and lower parts of the river [12]. Several other publications are devoted to the study of the diversity of algae, including diatoms, in the rivers and reservoirs of Uzbekistan located in the catchment area of the Zarafshan River. While some references do not provide a link to a specific collection site [13,14] and were published about a hundred years ago in Russian, they may have only historical value. Others, published in Russian and in the form of abstracts [15,16,17], were included in the general reference [18] that was used by us as one of the sources of the biodiversity data within the following published paper [19]. A short analysis of the middle part of the river diatom flora was presented in [20]. The hydrochemical data on the section of the Zarafshan River that interests us are discussed separately in the work of Kulmatov et al. [21].
The aim of our study was a comprehensive assessment of the ecological state of the Zarafshan River, which is an environment-forming river for Uzbekistan, based on the species composition of diatoms and environmental indicators using statistical methods and bioindication in the conditions of a transboundary river in a semi-desert climate. Ecological mapping of the quality of river waters for organic and toxic pollution will link the chemical and biological data of the study to the landscape of the transboundary river.

2. Materials and Methods

2.1. Description of Study Site

The Zarafshan River originates at the junction of three mountain systems—the Turkestan, Zarafshan, and Gissar (Alai) ranges from the Zarafshan glacier at an altitude of about 5000 m outside of Uzbekistan. Zarafshan Valley is the largest intermountain depression in Central Asia. Its length is about 877 km [22].
The initial section of the current, about 300 km long, runs in a narrow and deep valley between the Turkestan (in the north) and Zarafshan (in the south) ranges (Figure 1). From the left southern side, it receives significant tributaries—the Fandarya, Kshtutdarya, and Magiandarya. The average annual water flow in this section fluctuates between 58–108 m3/s. The water level is high in July and August, and low in April [22].
The Zarafshan River, after merging with Magiandarya, passes through the territory of Tajikistan to the west to Penjikent and turns to the northwest into the territory of Uzbekistan (Figure 1). Below Penjikent, on the territory of Uzbekistan, a flat section of the course begins, where not one single significant tributary flows into the Zarafshan until the end of the river [22].
In Uzbekistan, the upper part of the riverbed has a high biodiversity, which is protected by the IUCN reserve. The Zarafshan State Reserve (Figure 1) was established in 1975 in the Samarkand region on the right bank of the Zarafshan River, 15 km from the city of Samarkand, at an altitude of 600 to 900 m above sea level. Its area is 2352 hectares, including a small area covered by forest of 868 hectares. The territory of the reserve extends for 35 km along the riverbank with a width of 150 m to 1400 m. Its main objective is to preserve, study, and restore the natural environment of forest plants and animals as well as the gene pool of rare and endangered plants and animals. The climatic conditions of the reserve are typical of the continental subtropics. The air temperature in summer reaches +4 °C, and in winter it drops to −27 °C. The average annual precipitation is 100–400 mm. The flora consists of trees, shrubs, and herbs such as poplar, willow, cypress, and chakanda. The reserve is home to 266 plant species, 172 bird species, and 8 fish species. The reserve protects the golden pheasant, and cage breeding has been studied. Since 2016, work has been underway in the reserve to acclimatize six Bukhara deer, and the work to breed this unique animal is being continued [23].
Further downstream, the riverbed is flat, has virtually no catchment area, and is constantly changing and anastomosing. Sampling points cover all three parts of the river on the territory of Uzbekistan (Table 1). As can be seen from the table, the altitude of sampling points in the upper part of the river is significantly higher and refers to its mountainous section. The other points are much lower, and the drop in altitude occurs smoothly, starting from the city of Samarkand to the confluence of the river with the Amu Darya River. In the middle part of the riverbed, the Zarafshan River divides into two approximately equal streams at stations 5 and 6, then reuniting into one river at station 7.

2.2. Material

For a full-scale analysis of the dynamics of diversity and assessment of water quality in the Zarafshan River, hydrochemical data from 7 of the 12 stations from UzHYDROMET (Hydrometeorological Service Center (Uzgidromet) under the Cabinet of Ministers of the Republic of Uzbekistan) [24] were used, as well as data from previously conducted studies of algae diversity by the authors and other researchers.
For stations 1 and 2 of the upper reaches of the Zarafshan River, the data on diatoms published by A.M. Muzafarov [1] were used, and only 233 taxa identified in the riverbed were selected from the list, excluding lakes and other water bodies.
In the middle reaches of the Zarafshan River basin at stations 3–6, the diversity of diatoms was studied by J. Toshpulatov together with K. Alimjanova in 2005–2011 and amounted to 218 species from 81 samples [15,18]. Diatoms in the lower reaches of the Zarafshan River were studied at stations 7–12 [19] during 2009–2015 in relation to pollutant influx and water quality, and 198 species were identified from 195 samples. Both series of sampling in the four seasons and species definition were performed under the supervision of K. Alimjanova in 2005–2019 and published in detail in [15,18,19]. Diatom samples were collected throughout the river within the borders of Uzbekistan at 12 sampling stations. Periphyton was collected by scraping with a scalpel or knife from underwater substrates, aquatic vegetation, or dead plant substrate at a depth of 0 to 50 cm along the riverbanks from an area of 10 cm2. Benthos samples were collected from the river bottom using improvised means. Samples were fixed in 4% neutral formaldehyde and transported to the lab in an icebox.
All these data on water chemistry and diatom diversity were combined by us into a database for this work. A list of species was compiled for each of the 12 stations. As a result, we have a set of hydrochemical data from state monitoring stations (2–7, 9) for analysis, as well as a set of biological data from stations 1–12, which we collected not only at state monitoring stations, but also in the upper reaches of the river near the border with Tajikistan, in the intervals between hydrochemical stations, and in the lower reaches of the river. Thus, biological data cover the river with a denser and more continuous network of monitoring stations.
The modern taxonomic names were updated with the help of algaebase.org [25]. The abundance of cells of each revealed species in each station community was assessed as scores from 1 to 6 according to a semi-quantitative method [26]. Index saprobity, S, was calculated according to each indicator species abundance and its species-specific value [27,28].

2.3. Methods

Bioindication properties of each identified species are taken from our collected database [28,29]. Bioindicator analysis was performed with species-specific ecological preferences of revealed taxa classified according to indicator systems [29,30]. Hydrochemical variables were classified from an ecological point of view [31]. Both hydrochemical and biological data were analyzed with the following statistical programs. Similarity trees were performed using the BioDiversity Pro 2.0 program [32]. The correlation network analyses were performed in JASP (Jeffreys’s Amazing Statistics Program) on the botnet package in R Statistica [33]. The heat map was constructed in the ExStartR program [34].
Calculation of the Water Ecosystem State Index (WESI) was performed for definition of the environmental impact to the diatom communities on each sampling station [31] as a function of the classification rank of Index S and rank N-NO3.
Index WESI = rank of Index S/rank N-NO3
where Rank S is the rank of water quality according to the range of Sládeček’s saprobity indices [27] calculated for the sampling site; Rank N-NO3 is the rank of water quality according to the range of nitric nitrogen concentration [28,31].
The index values vary from 0 to 9. If WESI is more than one, the aquatic ecosystem stayed in good condition, whereas for affected communities exposed to toxic pollution inhibiting photosynthesis, WESI is below one.
The integral River Pollution Index (RPI), according to Sumita [35], was calculated for chemical and biological data in the sampling sites and the distance between them (Table 1) according to equation:
R P I d = ∑ 1 n D i + D j × l 2 L
where Di, Dj are the variable values of entire format units for the adjacent sites i, j; l is the distance between two adjacent sites (km); and L is the total river length.

3. Results

3.1. Physicochemical Properties of the Zarafshan River Water

Averaged chemical variables over stations 2–7 and 9, defined by [24] for the period of 2009–2015 in the Zarafshan River, are represented in Appendix A Table A1. Appendix A Table A1 shows that the amplitude of fluctuations in the values of the main environmental variables remains relatively constant throughout the year, as indicated by the value of the standard deviation. The value of pesticides was minimal. However, the pollution variables Total Suspended Solids (TSS), Total Dissolved Solids (TDS), and Chemical Oxygen Demand (COD) varied widely in years of monitoring.
The most important thing in this study is to consider changes in the indicators of the environment at the river stations. Even though not all the stations that we examined were represented in the monitoring system, there is still data for each of the three sections of the river. Figure 2 shows the change in the main indicators at the river stations. It is evident that all the stations in the upper and middle reaches of the river have similar and low indicators, whereas starting from station 6 their values increase significantly, excluding oxygen, which in contrast decreases.
We examined separately the dynamics of the macro indicators in Figure 3. COD, TSS, and TDS are critical variables because their values are dramatically changed down the river. The values of mineral pollution increased significantly, several times, starting from station 6, which belongs to the northern branch of the middle reaches of the river.

3.2. Biological Characteristics of the Zarafshan River

The diversity of diatoms in the Zarafshan River, which crosses the entire territory of Uzbekistan, amounted to 428 species (Appendix A Table A2). The diatom species distribution over the sampling stations shows the greatest species richness from 96 to 109 at stations 1, 11, and 12. Here, as well as at stations 5–7 and 9, the abundance of algae in the communities was also the greatest. Despite significant fluctuations in the species composition of diatom communities at the river stations, the species richness in the river sections remains approximately the same: upper—185 species, middle—200 species, and lower—194 species (Appendix A Table A2). The most abundant species in the upper part were Diploneis ovalis and Odontidium hyemale that were presented across all stations of the part. The middle part communities were dominated by Diatoma vulgaris across most of the sampled stations. In the lower part stations, Navicula rostellata prevailed in most communities.
Figure 4 shows comparative fluctuations in the variables of the biotic part of the Zarafshan River ecosystem. The smallest number of species was at station 4, and it was also low at stations 8 and 10. The trend line for this species distribution sags in the middle part of the river, showing a vulnerable area. Despite significant variability in the abundance of diatoms in communities, the trend line shows a significant increase in abundance towards the mouth of the river. At the same time, the saprobity index, S, varied within the 2 and 3 water quality classes, and its trend had a slight increase in the middle of the river.

3.3. Bioindicators

Based on the database of identified species and their ecological preferences (Appendix A Table A2 and Table A3), indicator taxa of diatoms were determined at 12 stations of the Zarafshan River. Diatom indicator species were grouped by three sections of the river according to nine groups of bioindicators (Figure 5). The proportion of benthic species increased downstream of the river (Figure 5a). Water temperature indicators showed water warming in the lower third of the river (Figure 5b). The proportion of slightly acidic and neutral water indicators increased noticeably, and the proportion of alkaliphiles increased (Figure 5c). A slight increase in the proportion of stagnant water species towards the river mouth corresponded to a decrease in water oxygen saturation (Figure 5d). The trend towards water salinization downstream was reflected by chloride indicators, with an increase in mesohalobes in the lower third of the river (Figure 5e). At the same time, the indicators of organic pollution of waters according to Watanabe [36] (diatoms only) showed a noticeable increase in the proportion of saproxenes, inhabitants of water unpolluted by organics, in the lower third of the river (Figure 5f). The indicators of the type of nutrition were 80–85% represented by autotrophs, but in the second and third parts of the river mixotrophs (hne, hce) appeared in the communities, the development of which is not hindered by the presence of toxicants (Figure 5g). A noticeable increase in the proportion of oligotrophy indicators downstream of the river shows a decrease in the trophicity of its ecosystems (Figure 5h).

3.4. Species Environment Relationships

Figure 6, Figure 7 and Figure 8 were constructed to compare the importance of chemical, biological, and combined data results at the same set of stations. It was the limited set of stations where chemical data were available that determined the order of data selection for all three plots. Therefore, statistical comparison of the data was performed using three combinations based on Appendix A Table A1 and Appendix A Table A3. To construct the similarity tree in Figure 6, only hydrochemical environmental parameters (Appendix A Table A1) were selected, which were available for seven stations only. It is evident that significant similarity was observed only for the upper stations from 1 to the southern channel of station 5.
The tree in Figure 7 included, in addition to Appendix A Table A1 data, also bioindicator parameters (Appendix A Table A3), but for the same seven stations. The similarity of the constructed Figure 6 and Figure 7 is obvious, indicating the predominance of chemical data in the assessments. Figure 8 is constructed using bioindicator data only, but for the same seven stations. A significant similarity of bioindicators is observed for stations 2, 5, 6, 8 and 9, while the data from stations 3 and 4 fall into separate branches. Stations 3 and 4 belong to the Samarkand region. This shows the importance of more detailed assessments of the bioindicators separately, but for the entire data set over all studied stations (Appendix A Table A3). Therefore, we continue the data comparison with other statistics. For a detailed analysis of the links between biodiversity and chemical data, graphs were constructed in the JASP program.
A statistical comparison of chemical and bioindicator variable values with JASP at seven stations of the Zarafshan River showed that the river can be divided into two sections (Figure 9). Cluster 1 combines the values at the stations of the upper and middle sections, while cluster 2 includes only the stations of the lower section of the river.
However, if all river stations for which data are available (St. 1–St. 12) are included in the analysis, then only biological indicators form the basis for the analysis. The JASP Network plot (Figure 10) groups biological data into two clusters. Cluster 1 includes the upstream stations and two middle-section stations 5 and 6, located on two parallel branches of the river. The remaining stations are united by cluster 2, which includes all the stations of the downstream section of the river plus two stations 3 and 4, related to the middle course of the river. Thus, the communities at stations 3 and 4, as well as 5 and 6, reflect the complexity of the impact of the environment around the city of Samarkand.

3.5. Integral Indices of Water Toxicity (WESI) and River Pollution (RPI)

Based on the available chemical and biological data, the WESI was calculated, showing the inhibition of photosynthesis in the studied communities at the river stations. The index was calculated considering that the river is divided into two branches and flows in one branch through station 5 and in the second branch through station 6, then merges. This is why in Figure 11, the index data are separate for stations 5 and 6. Figure 11 shows that the communities at the lower reaches of the river stations 7 and 9 were inhibited, since the index was less than one. The remaining communities vegetated successfully, but at station 5 of the northern branch of the river they experienced some toxic effect, which was higher than at station 6.
Although the toxic heavy metal pollution is particularly high at the river headwaters at station 2 and then at the end of the riverbed at stations 7 and 9, the toxic organic pollution fluctuates significantly depending on the source (Appendix A Table A1). The fluctuation of pesticides Alpha-HCH (Hexachlorocyclohexane) and DDT (dichloro-diphenyl-trichloroethane) is particularly noticeable, with its highest concentration at the river headwaters at station 2 and then repeated at stations 4, 5, and 7, where the drainage channels flow in. At the same time, the pollution caused by dissolved organic matter is not as high. The calculated saprobity indices, S, characterize the studied sections of the river according to water quality class from 2 to 3. Based on these data, we compiled a map of organic pollution class and accordingly colored not only the riverbed but also the section of the catchment basin related to each station. Figure 12a shows that organically enriched waters of Class 3 come from the out-border area of the Zarafshan River. Stations of the upper (3, 4, and 6) as well as the middle parts of the river (8, 9, and 10) were also marked as Class 3 in terms of water quality. All other parts of the river basin contain low organic matter in its water. We did not reveal any stations with waters of Classes 4 and 5. At the same time, the map of WESI distribution over the river (Figure 12b) takes attention to the middle part of the basin with stations 7, 8, and 9. This is part of the river basin with a narrow catchment area but is very enriched by settlements and saturated with enterprises discharging wastewater from processes with heavy metals. Both these maps show that the toxic effect in the middle part of the Zarafshan River landscape is due to the influence of metal discharges, but not organic pollution. Overall, the river has a high potential for self-purification, as can be seen on the maps in Figure 12, where the downstream stations already contain higher-quality non-toxic water.
The integrated index of river pollution, RPI, was calculated based on the available chemical and biological data, also considering the division of the river into two branches with stations 5 and 6. Table 2 shows in bold the index values for the river parameters passing through station 6, which exceed those for the southern branch of the river passing through station 5. The greatest difference in the RPI indices was observed for TSS and TDS. Apparently, the excesses of the index for zinc, copper, phenols, fluorine, and detergents are associated with the influx of turbid and salted waters. The excesses of nitrites and COD indicate that the northern branch of the river is actively decomposing the influx of both organic and mineral pollutants. However, the relatively close values of the index for the abundance and number of species in both streams passing through the northern and southern branches of the river indicated that, in general, the river ecosystem successfully copes with the pollution entering the northern branch and the impact is leveled out.

4. Discussion

For the first time, a study was conducted on the dynamics of environmental parameters and diatom communities along the entire length of the Zarafshan River, which crosses the territory of Uzbekistan from the border with Tajikistan to its confluence with the Amu Darya. The transboundary river has not been previously fully surveyed. However, according to the hydrochemical data of the upper transboundary section, a study was conducted [21] and showed a high water quality, with an excess of some metals as echoes of discharges from ore processing industries in Tajikistan. A complete list of algae inhabiting the riverbed in Uzbekistan and responsible for the self-purification processes of waters has not yet been compiled. Separate works were devoted to algal communities of some sections of the river, its tributaries, and reservoirs of its subordinate system [18,20]. Our study identified 428 species of diatoms, 98% of which can be used as indicators for nine environmental parameters for water quality monitoring that have not been used by UzHydromet up to now.
Our research in rivers has shown that the RPI can show the dynamics of chemical or biological indicators, but also indicate those places in the river channel where negative changes occur [37]. The RPI showed that the northern channel introduces noticeable pollution into the riverbed, of which the TSS values had the greatest gradient compared to the southern channel. Along with turbidity, the influx of metals and phenols was detected. However, in general, the dynamics of hydrochemical indicators underwent sharp changes at the stations of the lower reaches of the river, where TSS and TDS increased sharply. However, the saprobity index, S, was generally within the limits of 2–3 water quality classes, which indicates a large influence of inorganic pollution, rather than organic matter
Statistical analysis also confirms this conclusion, since separately calculated similarity coefficients for chemical data, for biological data, and for both together show the prevalence of the influence of chemical components of the ecosystem on its species composition. An assessment of the ecological state for the lower third of the river, carried out by us earlier [19], showed the sources of pollution and how the river ecosystem responded to their entry into the water, especially highlighting the stations near Navoi and Khatirchi. Arsenic and zinc entries were detected here. However, when analyzing the entire Uzbek section of the river, our attention was drawn to the stations near the city of Samarkand, where the middle reaches of the river begin. Bioindicator analysis of river communities, divided into three sections, showed that as the temperature and salinity of the waters as a whole increase towards the mouth of the river, oxygen and pH decrease. Organic pollution also decreases down the river. Communities tend to occupy substrates downriver rather than inhabit the water column and were mostly autotrophs. Along the river, the water became more oligotrophic, remaining at quality Class 2–3.
Alarming levels of some of the legacy persistent organic pollutants (POPs) may pose adverse effects on the aquatic species dwelling in the riverine communities [38]. However, in the case of the Zarafshan River in the Uzbekistan part, it can be seen that the Zarafshan Nature Reserve plays a very important role in decreasing the risk of pesticide impact.
In the nearby region of the southern Caspian Sea, rivers flowing in from the south [39] have, as in our case, fluctuations in water quality, and the most polluted stations there were, on the contrary, in the upper, mountainous sections, which the authors associate with anthropogenic activity. The presence of heavy metals is also characteristic of mountainous sections of rivers in southern Europe, since it is associated with the presence of industry in the region [40]. In large European rivers, the combined effects of both heavy metals and pesticides lead to the suppression of biodiversity because of the combined toxic effects [38,41]. Among the large rivers in the immediate region, studies on hydrochemical indicators are known in the Tigris River, Iraq [42]. Here, the opposite trend of increasing organic pollution downstream and deteriorating water quality is noted. In the case of the Zarafshan River, we see a trend towards improving water quality in both hydrochemical and biological indicators. Even though pollution is significantly greater in the northern branch of the middle course that is reflected in a decrease in biodiversity and the abundance of diatoms, and comes from subsequent industrially saturated stations, the general state of the river ecosystem, as a whole, is improving. It can be assumed that the protected area of the Zarafshan Nature Reserve, which reduces transboundary pollution, plays a significant role in this.
Our data on indicator assessments were obtained for the first time for a transboundary landscape-forming river flowing through the entire territory of Uzbekistan. Currently, the catchment area of the Zarafshan River has a very limited volume even in the flat sections of the river. The influx of pollutants is, therefore, limited by the properties of the landscape, i.e., it comes from the mountainous transboundary area of the upper reaches and the water flows of the irrigation system of the middle and lower reaches. At the same time, the analysis of water for irrigation reduces the water content of the river and leads to a decrease in the self-purification capacity of its ecosystem. This is also facilitated by the high turbidity of the water, which suppresses the development of algae. Our previous studies in the Central Asian region have demonstrated the effectiveness of ecological mapping of water quality indicators and indices for the Arys River basin in Kazakhstan [11]. Our first basin-based water quality map for the transboundary Zarafshan River showed problem areas where elevated pollutant levels were also detected and, therefore, the effectiveness of mapping for future monitoring. Water quality monitoring in Uzbekistan is currently carried out only by hydrochemical indicators. Our work has shown that biological indicators should also be included in the monitoring system, since transboundary impacts and internal sources lead to a decrease in diversity. For this purpose, we have already created a database of diatom indicator algae for the largest river, the Zarafshan.

5. Conclusions

For the first time, we compiled a general list of 428 diatom species in the Zarafshan River and conducted a comprehensive ecological assessment of water quality and the state of the aquatic ecosystem based on their communities using bioindication and statistics. Of the entire list, 91 percent of the species were indicators for 9 environmental parameters. Community at stations 3 and 4, as well as 5 and 6, reflect the complexity of the impact of the environment around the city of Samarkand and further in the middle reaches of the river. The indicator species reflect the dynamics of water quality in the river downstream, where organic pollution and general toxic impact are not yet tracked by the monitoring system. Analysis of the distribution of bioindicators, organic pollution indices and WESI, as well as statistics, show an increase in salinity and turbidity and a decrease in organic pollution downriver. At the same time, the Navoi section is also a source of water acidification. Our analysis shows that nutrients and heavy metals, as well as phenol and pesticides pollution, enter the river from various sources mainly in the middle reaches of the river. The small catchment area in a dry climate can be regarded as a positive factor, reducing the irrigation area and the pollution coming from it. The integrated index of river pollution RPI shows most pollution comes from the northern canal of the river in the middle reaches. For the first time in Uzbekistan, ecological mapping of the river was used to visualize problem areas of the river. Based on the results of bioindication, an increase in self-purification with an increase in the species richness and number of diatoms in the middle section of the Zarafshan River was found. This indicates that the river ecosystem is successfully coping with incoming pollutants. Such a conclusion could not be made based on chemical analysis of the water alone. This allowed us to recommend the inclusion of biological indicators and the expansion of state monitoring points to the lower section of the Karakul.

Author Contributions

Conceptualization, K.M. and S.B.; methodology, S.B.; software, S.B.; validation, K.M. and K.A.; formal analysis, K.M. and S.B.; investigation, K.M. and K.A.; data curation, K.M., K.A. and S.B.; writing—original draft preparation, S.B.; writing—review and editing, K.M., K.A. and S.B.; visualization, S.B.; supervision, S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no funding.

Data Availability Statement

Data are available in published paper in the journal site with citation.

Acknowledgments

We are grateful to the Israeli Ministry of Aliyah and Integration for partial support of this research.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Averaged chemical variables over stations in the Zarafshan River according to [24] with standard deviation.
Table A1. Averaged chemical variables over stations in the Zarafshan River according to [24] with standard deviation.
Station22334455667799
VariableAverageMax.AverageMax.AverageMax.AverageMax.AverageMax.AverageMax.AverageMax.
O2 mg L−18.72 ± 1.1610.368.7 ± 1.1410.316.3 ± 2.099.256.3 ± 2.099.258.415 ± 1.289.697.295 ± 2.179.546.983 ± 1.698.44
BOD, mgO L−10.53 ± 0.300.950.8 ± 0.281.20.84 ± 0.401.40.84 ± 0.401.40.86 ± 0.241.11.638 ± 0.972.72.86 ± 0.993.8
COD, mgO L−13.32 ± 1.465.393.29 ± 1.485.393.3 ± 1.95.983.3 ± 1.905.985.71 ± 1.767.4712.438 ± 6.4919.731.125 ± 6.9340.9
N-NH4, mg L−10.03 ± 0.040.080.04 ± 0.030.080.03 ± 0.010.070.03 ± 0.030.070.1 ± 0.050.150.043 ± 0.030.070.165 ± 0.080.25
N-NO2, mg L−10.86 ± 0.641.770.59 ± 0.331.050.8 ± 1.653.141.65 ± 1.653.142.965 ± 1.594.550.025 ± 0.010.0350.12 ± 0.060.178
N-NO3, mg L−10.005 ± 0.120.170.007 ± 0.010.0280.007 ± 0.010.0230.007 ± 0.010.0230.025 ± 0.010.0372.688 ± 2.275.574.83 ± 3.288.79
Fe, mg L−10.01 ± 0.040.060.01 ± 0.030.050.01 ± 0.010.030.01 ± 0.010.030.025 ± 0.020.040.03 ± 0.030.070.09 ± 0.070.18
Cu, mcg L−11.60 ± 1.343.52 ± 1.1441.9 ± 1.273.71.9 ± 1.273.74.65 ± 2.156.85.25 ± 3.168.96.1 ± 2.108.2
Zn, mcg L−12.0 ± 1.343.92.1 ± 2.195.22.3 ± 2.475.82.3 ± 2.475.84.35 ± 2.056.45.65 ± 3.619.74.275 ± 0.625.5
Phenols, mg L−10.001 ± 0.00.0050.002 ± 0.00.0060.001 ± 0.00.0040.001 ± 0.00.0040.006 ± 0.0030.0090.005 ± 0.00.0090.002 ± 0.00.005
Oil, mg L−10 ± 0.0070.010.01 ± 0.00.010.01 ± 0.050.080.01 ± 0.050.080.03 ± 0.020.050.02 ± 0.030.050.03 ± 0.050.09
Detergents, mg L−10.01 ± 0.010.020.01 ± 0.0010.010 ± 0.010.010 ± 0.010.010.01 ± 0.010.020.015 ± 0.010.050.005 ± 0.010.02
TSS, mg L−1277.3 ± 867.51504.2249.8 ± 669.51196.6230.7 ± 654.31156230.7 ± 654.31156993.8 ± 629.21623591 ± 461.211181028.1 ± 477.82316
DDT, mg L−10 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.00
Alpha-HCH, mcg L−10.001 ± 0.00.0070 ± 0.000 ± 0.00.0040 ± 0.00.0040 ± 0.000 ± 0.000.002 ± 0.00.004
Gamma-HCH, mcg L−10 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.000 ± 0.00
Cr VI, mcg L−10.1 ± 0.210.40.3 ± 0.180.050.4 ± 0.4210.4 ± 0.4210.3 ± 0.00.30.825 ± 0.601.51.275 ± 0.501.8
F, mg L−10.17 ± 0.060.260.19 ± 0.080.30.16 ± 0.060.250.16 ± 0.060.250.36 ± 0.10.460.693 ± 0.2410.865 ± 0.201.02
As, mcg L−10.9 ± 1.483.000.5 ± 1.142.50.3 ± 1.2020.3 ± 1.2021.35 ± 0.852.23.125 ± 5.67110 ± 0.00
TDS, mg L−1305 ± 42.2364.7300.5 ± 79.1412.3292.6 ± 63.1381.9292.6 ± 63.1381.9515.75 ± 171.4687.1728.8 ± 170.6878.11710.8 ± 342.62014.5
Table A2. Diatom species distribution over the sampling stations and the river parts of the Zarafshan River with indicator properties. Upper—stations 1 and 2; Middle—stations 3–6; Lower—stations 7–12.
Table A2. Diatom species distribution over the sampling stations and the river parts of the Zarafshan River with indicator properties. Upper—stations 1 and 2; Middle—stations 3–6; Lower—stations 7–12.
TaxaUpperMiddleLower123456789101112HabTOXYHALpHDIndex S SAPAUT-HETTRO
Achnanthes coarctata (Brébisson ex W.Smith) Grunow 1880011000001100001B-st-strhlind-0.20oatsot
Achnanthes conspicua var. brevistriata Hustedt 1930010001000000001B--eh------
Achnanthes dispar var angustissima (Jasnitsky) Sheshukova 1950001000000000001----------
Achnanthes gibberula var. interrupta Poretzky and Anisimova 1933110110000000000----------
Achnanthes neoskortzowii Simonsen 1987001000000000011B--iind-----
Achnanthes parvula Kützing 1844010000000000010B--mhalf-2.00batsme
Achnanthes profunda Skvortzov 1937001000000000010----------
Achnanthes striata Skvortzov and K.I. Meyer 1928001000000000001B--iind-----
Achnanthidium exile (Kützing) Heiberg 1863001000000000010B-strialbsx1.80oatsom
Achnanthidium minutissimum (Kützing) Czarnecki 1994101010000101100P-Betermst-striindes0.95batee
Achnanthidium nodosum (Cleve) Tseplik and Chudaev 2020001000000000110B--hbacf-1.00o-ot
Achnanthidium pyrenaicum (Hustedt) H. Kobayasi 1997001000000010100Btemp-mhalfes1.10oate-
Actinella punctata F.W. Lewis 1864100010000000000Btemp-hbacf-1.00o-ot
Adlafia minuscula (Grunow) Lange-Bertalot 1999011000001001000P-B. aertempst-strialfes2.80bhceot
Altana cingens (Skvortzov) Kulikovskiy, Metzeltin and Lange-Bertalot 2012010000000100000B--i------
Amphipleura pellucida (Kützing) Kützing 1844100100000000000P-B-stialfsp0.80bateom
Amphora ovalis (Kützing) Kützing 1844 var. ovalis111100000101001Btempst-strialfsx1.50batee
Amphora commutata Grunow 1880101100000000000B--hl. mhalf---atse
Amphora costulata Skvortzov 1937010000100000010B--i--1.00o--
Amphora gracilis Ehrenberg 1843010000001000000B---------
Amphora libyca Ehrenberg 1841001000000000001Btempstialfes1.50o-bateom
Amphora mongolica Østrup 1908100100000000000B--iind-----
Amphora ovalis var. gracilis (Ehrenberg) Van Heurck 1885001000010000001B--ialfsx1.50o-b--
Amphora pediculus (Kützing) Grunow 1875001000000000001Btempstialfes1.70bateme
Amphora proteus var. baikalensis Skvortzov 1937001000000000010----------
Amphora robusta W. Gregory 1857010000000100000Btemp-eh------
Amphora subconstricta Levkov 2009001000000000001B--ialf-----
Aneumastus tusculus (Ehrenberg) D.G. Mann and A.J. Stickle 1990111010000011000P-B-stialb-0.90bateo-e
Anomoeoneis costata (Kützing) Hustedt 1959001000000000010B-st-strmhalf-2.70a-ohnee
Aulacoseira ambigua (Grunow) Simonsen 1979100000000100000Ptempst-strialfsp1.70b-oateom
Aulacoseira granulata (Ehrenberg) Simonsen 1979 var. granulata110110000000010P-Btempst-strialfes2.00batee
Aulacoseira granulata var. angustissima (O.Müller) Simonsen 1979010000000000010Ptempst-strialfes2.10batee
Aulacoseira italica (Ehrenberg) Simonsen 1979100100000000000P-Bcoolst-striindes1.45bateme
Bacillaria paxillifera (O.F.Müller) T.Marsson 1901110000010100010P-B-st-strmhindes2.30aatee
Belonastrum berolinense (Lemmermann) Round and Maidana 2001010000010000000P-B-st-strhlalf-2.20batehe
Berkeleya fragilis Greville 1827010000010000000----------
Brachysira microcephala (Grunow) Compère 1986001000000100000B-st-strialfsx1.30batsom
Brachysira serians (Brébisson) Round and D.G.Mann 1981100000010000000B-st-strhbacb-0.20oatsot
Brebissonia lanceolata (C.Agardh) R.K.Mahoney and Reimer 1986110110001000000P-Btemp-hlalf-2.00x-o--
Caloneis amphisbaena (Bory) Cleve 1894111000010100011B-st-strialf-2.30aatee
Caloneis bacillum (Grunow) Cleve 1894111010001000000Btempst-strialfes1.30batsme
Caloneis budensis (Grunow) Krammer 1985010000010000000B-sthlalf-----
Caloneis dubia Krammer 1987001000010000001P-B-st-strhb--1.00o-ot
Caloneis fossilis A.Cleve 1915001000000100010-warm-eh------
Caloneis leptosoma (Grunow) Krammer 1985001000000101010B-striind-1.00oatsom
Caloneis molaris (Grunow) Krammer 1985001000000001000B-striindes1.00o-ot
Caloneis silicula (Ehrenberg) Cleve 1894010000010000000Bwarmstiindsp1.30oatsom
Campylodiscus echeneis Ehrenberg ex Kützing 1844001000011000010P-stmh------
Campylodiscus lacus-baikali Skvortzov 1937010000010000000B--iind-----
Campylodiscus rutilus Skvortzov 1937010000010000000----------
Cavinula scutiformis (Grunow) D.G.Mann and A.J.Stickle 1990010000001000000B--i------
Chamaepinnularia krookii (Grunow) Lange-Bertalot and Krammer 1999010000011000000P-B-aerialf-1.00oatsom
Cocconeis diminuta var. intermedia Kisselev 1932010000000100000----------
Cocconeis disculus (Schumann) Cleve 1882001000000001000B-st-strialfes0.70batsme
Cocconeis lineata Ehrenberg 1849101100010000001P-Btempst-strialfsx1.20batee
Cocconeis neodiminuta Krammer 1990011000000011010P-Btempst-strialfsx0.90batsme
Cocconeis pediculus Ehrenberg 1838010110000000010B-sthlalf--batee
Cocconeis placentula Ehrenberg 1838 var. placentula110110000100000P-Btempst-strialfes1.35oateme
Cocconeis placentula var. euglypta (Ehrenberg) Cleve 1895101000000001001P-Btempst-strialfsx1.30bateom
Cocconeis placentula var. intermedia (M.Peragallo and Héribaud) Cleve 1895100000010000000B-st-strialf-1.40o-bateot
Cocconeis placentula var. rouxii (Héribaud and Brun) Cleve 1895010000001000010B--ialf-1.40o-b--
Cocconeis skvortsovii Sheshukova-Poretskaya 1951010000000100000B--ialb-----
Cosmioneis pusilla (W.Smith) D.G.Mann and A.J.Stickle 1990010000000100000P-B. aer-st-strhlindsp1.80o-aatsom
Craticula halophila (Grunow) D.G.Mann 1990 var. halophila101100000000100Btempst-strmhalfes3.00aatee
Craticula halophila var. subcapitata (Østrup) Czarnecki 1995001000000001100B-st-strmhalfes----
Craticula simplex (Krasske) Levkov 2016001000000000001B--ialb-----
Crenotia thermalis (Rabenhorst) Wojtal 2013001000000000010Betermst-strmhindsx0.30o-om
Ctenophora pulchella (Ralfs ex Kützing) D.M.Williams and Round 1986 var. pulchella001000000011000P-B. Eptempst-strmhalfsx2.30aatee
Ctenophora pulchella var. lacerata (Hustedt) Bukhtiyarova 1995110010001000000B--mh----hne-
Ctenophora pulchella var. lanceolata (O’Meara) Bukhtiyarova 1995001000000011000P-B--Ialf-2.00bhne-
Cyclostephanos dubius (Hustedt) Round 1988011100001100101P-Btempst-strhlalfes2.00aatee
Cyclostephanos mansfeldensis Houk. Kleen and H.Tanaka 2014001000000000010P--iind-----
Cyclotella choctawhatcheeana Prasad 1990001000000000001P--hl------
Cyclotella comta var. spectabilis A.Cleve 1915001000000001000----------
Cyclotella distinguenda Hustedt 1928 var. distinguenda001000000011001P-strhlalf-1.30o-om
Cyclotella distinguenda var. unipunctata (Hustedt) Håkansson and J.R.Carter 1990001000000001010P--iind-----
Cyclotella melosiroides (Kirchner) Lemmermann 1900001000000011010P--i------
Cyclotella meneghiniana Kützing 1844101100010001111P-Btempst-strhlalfsp2.80ahnee
Cyclotella operculata var. mesoleia Grunnow 1878011000000000010P--iind-----
Cylindrotheca closterium (Ehrenberg) Reimann and J.C.Lewin 1964001000000000001B--ehalf-2.00bhne-
Cymatopleura angulata Greville 1862010000010100000B--ialf-----
Cymatopleura elliptica (Brébisson) W.Smith 1851100110000000000P-Btempst-strialf-1.40batee
Cymbella lanceolata C.Agardh 1830 var. lanceolata001000000001110Bcool-iindsx----
Cymbella affinis Kützing 1844101000010000001B--i------
Cymbella aspera (Ehrenberg) Cleve 1894001000000000001B--ialf-1.00o-ot
Cymbella bergii Kisselev 1932001000000000001----------
Cymbella cistula (Ehrenberg) O.Kirchner 1878 var. cistula101110000001001B--iind-----
Cymbella cistula var. maculata (Kützing) Van Heurck 1885010011101000000----------
Cymbella cymbiformis C.Agardh 1830111101001000000Btempst-strialfsx2.00batsom
Cymbella helvetica var. curta Cleve 1894011000000000001Btempst-striind-0.60batsme
Cymbella helvetica var. helvetica Kützing 1844001000000000001----------
Cymbella helvetica var. punctata Hustedt 1922001000000000001B--i------
Cymbella lacustris f. baicalensis Skvortzov and K.I.Meyer 1928010000001000000----------
Cymbella laevis Nägeli 1863011000000000010B--ohalf-----
Cymbella lanceolata var. notata Wislouch and Poretzky 1924111000000000001Btempst-strialfes2.50b-aatee
Cymbella obtusiuscula Kützing 1844100010001000000Btempstialf-1.20o-om
Cymbella parva (W.Smith) Kirchner 1878110001100000001B--iind-1.00o--
Cymbella proschkinae Muzafarov 1965100000001000000----------
Cymbella skvortzovii Skabichevskij 1936011000000000001B-stIindsx2.00batem
Cymbella stuxbergii (Cleve) Cleve 1894100110000000000B---------
Cymbella tartuensis Molder 1937001000000101010B--iind-----
Cymbella tumida (Brébisson) Van Heurck 1880 var. tumida011001010001010B---------
Cymbella tumida var. borealis (Grunow) Cleve 1894010000110000000Btempst-strialfsx2.20batsme
Cymbella tumidula Grunow 1875111000010000001B--i------
Cymbella turgidula Grunow 1875011001000100001P-B-strhbind-1.00oatsot
Cymbopleura amphicephala (Nägeli ex Kützing) Krammer 2003100000001000000B-st-striind-----
Cymbopleura austriaca (Grunow) Krammer 2003011000010000001B--iind-1.00o-ot
Cymbopleura lata (Grunow ex Cleve) Krammer 2003001000000000010B--iind-1.00o-ot
Cymbopleura naviculiformis (Auerswald ex Heiberg) Krammer 2003111010000001011Btempst-striind-----
Denticula elegans Kützing 1844110110000100000B--ohalf-2.00b--
Denticula tenuis Kützing 1844110000000100000B-aerhl-es1.00oatse
Denticula tenuis var. crassula (Nägeli ex Kützing) West and G.S.West 1901100000000100000B-striindsx0.30oatsm
Diatoma elongata (Lyngbye) C.Agardh 1824 var. elongata100000010000000P-B---ind--aatsme
Diatoma elongata var. pachycephala (Grunow) Hustedt 1931100110010000000----------
Diatoma moniliformis subsp. ovalis (F.Fricke) Lange-Bertalot. Rumrich and G.Hofmann 1991110100000000010P-Btempst-strialf-0.40x-o--
Diatoma tenuis C.Agardh 1812111000001000001B-----1.30o-om
Diatoma vulgaris Bory 1824 var. vulgaris111111101101011P-Btempst-strhlalf-2.40b-a-om
Diatoma vulgaris var. brevis Grunow 1862100110000000000P-Btempst-strialf-2.40b-a--
Diatoma vulgaris var. linearis Grunow 1881100110001000000B----sx2.20bateme
Diatomella balfouriana Greville 1855010000001000000B-----0.70oatsm
Diploneis smithii (Brébisson) Cleve 1894 var. smithii001000000000001B-----1.00o-ot
Diploneis smithii var. pumila (Grunow) Hustedt 1937011100000000101B--mhalf-----
Diploneis boldtiana Cleve 1891100110000000000B--mh------
Diploneis domblittensis (Grunow) Cleve 1894100000010000000B--hlalb-----
Diploneis ovalis (Hilse) Cleve 1891100110001000000B--oh-sx0.90oatsme
Diploneis subovalis var. baikalensis Skvortzov010000001000000----------
Discostella stelligera (Cleve and Grunow) Houk and Klee 2004001000000011010Ptempst-striind-2.70a-o--
Dorofeyukea grimmei (Krasske) Kulikovskiy and Kociolek 2019100010000000000---eh------
Encyonema ventricosum (C.Agardh) Grunow 1875110000010000010B-st-striind---ate-
Encyonema caespitosum var. ovatum Grunow 1875110100000000001------1.30ohne-
Encyonema elginense (Krammer) D.G.Mann 1990101110000001001Btempstialfes1.40o-b--
Encyonema hebridicum Grunow ex Cleve 1891100100000000000B---acf-1.00o-ot
Encyonema leibleinii (C.Agardh) W.J.Silva. R.Jahn. T.A.V.Ludwig and M.Menezes 2013110011000000001B-----1.00oatsot
Encyonema minutum (Hilse) D.G.Mann 1990001100010001000B--ialf-0.30x--
Encyonema perpusillum (A.Cleve) D.G.Mann 1990100000000000000B-----1.00o--
Encyonema ventricosum var. hankensis (Skvortzov) Rodionova and Pomazkina 2014010000000100000----------
Encyonopsis falaisensis (Grunow) Krammer 1997011000000011010----------
Encyonopsis microcephala (Grunow) Krammer 1997100000000000010B-----1.00o-ot
Entomoneis alata (Ehrenberg) Ehrenberg 1845101000000000011P-B-stmhalf-2.50b-a--
Entomoneis japonica (Cleve) K.Osada 2002001000000000001----------
Entomoneis ornata (Bailey) Reimer 1975001000000011000B-st-strialf-2.00bhne-
Entomoneis paludosa (W.Smith) Reimer 1975 var. paludosa001000000001000P-B--mhalf-----
Entomoneis paludosa var. duplex (Donkin) Czarnecki and D.C.Reinke 1982001100000001001----------
Entomoneis paludosa var. subsalina (Cleve) Krammer 1987001000000001001B--hl--1.20o-batsom
Eolimna minima (Grunow) Lange-Bertalot. nom. illeg. 1998001000000000010Btemp-hlalf-----
Epithemia adnata (Kützing) Brébisson 1838110110000100000Btempst-strialb-1.20o--
Epithemia argus var. angusta Fricke 1904010000010000000B--iindes0.70o-xhnem
Epithemia operculata (C.Agardh) Ruck and Nakov 2016110110000000000P-stiindes2.00b--
Epithemia parallela (Grunow) Ruck and Nakov 2016100000010000000P-B-----1.30o--
Epithemia turgida (Ehrenberg) Kützing 1844100000010000000Btempst-strialf-1.10---
Eucocconeis austriaca (Hustedt) Lange-Bertalot 1999010000011000000B--ialf-0.20xatsot
Eucocconeis depressa (Cleve) Lange-Bertalot 1999010100000000000B--hbacf-1.00o-ot
Eucocconeis elliptica Saveljewa-Dolgowa 1925010000010100000B--iindsx1.00o-ot
Eucocconeis flexella (Kützing) F.Meister 1912100110000000000Btempstrmhind-----
Eunotia exigua (Brébisson ex Kützing) Rabenhorst 1864 var. exigua100110000000000P-B. aertempst-strhbacb-1.00o-ot
Eunotia exigua var. bidens Hustedt 1930010000000100000B--hbacbes0.45x-oateo-e
Eunotia glacialis F.Meister 1912001000000000001B-strhbacf-0.60o-x--
Eunotia lunaris var. capitata (Grunow) Schönfeldt 1907100000010000000B-stiind-----
Eunotia minor (Kützing) Grunow 1881001000000000001Btempst-strhbacf-----
Eunotia pectinalis (Kützing) Rabenhorst 1864001000000000001B-st-striacfsx0.50x-o-ot
Eunotia praerupta Ehrenberg 1843100000000100000P-Bcoolst-strhbacf-0.30x--
Eunotia pseudopectinalis Hustedt 1924001000000000001Bcoolstrhbacf-1.00o-ot
Eunotia robusta Ralfs. nom. illeg. 1861100000000100000B-sthbacf-1.00o-ot
Eunotia tenella (Grunow) Hustedt 1913010000010000000Btempst-strhbacf-----
Eunotia vanheurckii R.M.Patrick 1958001000000000001Btempst-striacf-0.50x-oatsot
Fallacia reichardtii (Grunow) Witkowski. Lange-Bertalot and Metzeltin 2000001000000000010P-B-st-strialfes2.70a-ohnee
Fallacia subhamulata (Grunow) D.G.Mann 1990001000000000001Btempstriind-----
Fragilaria capucina Desmazières 1830 var. capucina111000101100010P-Btempst-striind-----
Fragilaria capucina var. lanceolata Grunow 1881100110000000000B---------
Fragilaria crotonensis Kitton 1869010000000100000P-Btempst-strialf-----
Fragilaria intermedia (Grunow) Grunow 1881100101000000000----------
Fragilaria septentrionalis (Østrup) Van de Vijver. C.E.Wetzel and Ector 2020100000010000000----------
Fragilaria vaucheriae (Kützing) J.B.Petersen 1938011000000001000P-B. Eptempst-strialf-----
Fragilariforma bicapitata (A.Mayer) D.M.Williams and Round 1988011001001001110P-B-st-strhbind-----
Fragilariforma nitzschioides (Grunow) Lange-Bertalot 2011010001010000000B--iindsx1.90o-aatsme
Fragilariforma virescens (Ralfs) D.M.Williams and Round 1988011000001001010P-Btempst-strhbind-1.00o-ot
Frustulia vulgaris (Thwaites) De Toni 1891100110000100000P-Btempst-strialf-1.00o--
Geissleria annulata (Grunow) Lange-Bertalot and Metzeltin 1996010000000000001----------
Geissleria schoenfeldii (Hustedt) Lange-Bertalot and Metzeltin 1996010000000100000Btempst-strialf----m
Gogorevia exilis (Kützing) Kulikovskiy and Kociolek 2020100000000000000Betermst-strialf-----
Gomphoneis clevei (Fricke) Gil 1989010001010000000B--ialf-2.70a-o--
Gomphonella calcarea (Cleve) R.Jahn and N.Abarca 2019100000010000000B-st-strialf-----
Gomphonella olivacea (Hornemann) Rabenhorst 1853110001010000000Btempst-strialf-2.30bateom
Gomphonema truncatum Ehrenberg 1832110100110000000Btempst-striind-2.00b--
Gomphonema acuminatum Ehrenberg 1832 var. acuminatum100110000100100Btempst-striind-0.80x-b--
Gomphonema acuminatum var. longiceps (Ehrenberg) N.Abarca and R.Jahn 2020100000000100000B-striind-----
Gomphonema angustatum (Kützing) Rabenhorst 1864100000000100000Btempst-striind-1.00o--
Gomphonema brebissonii Kützing 1849001100000000011B-stiind----m
Gomphonema capitatum Ehrenberg 1838001000000000010Btempstialf-1.20o-om
Gomphonema gracile Ehrenberg 1838001000000000110Btempst-strialf-----
Gomphonema grunowii R.M.Patrick and Reimer 1975101110000001001Btemp-ialfes0.80x-batsm
Gomphonema intricatum Kützing 1844101000000011110B-st-striind-----
Gomphonema lagenula Kützing 1844001000000000010B------batee
Gomphonema lanceolatum var. capitatum Skvortzov 1937010000000000001B--iind-1.30oatsot
Gomphonema micropus Kützing 1844100000010000000Btempst-striind-1.10---
Gomphonema olivaceum var. minutissimum Hustedt 1930100000010000000B-strialf-----
Gomphonema parvulum (Kützing) Kützing 1849101000010001110Btempst-striind-0.70o-xatsot
Gomphonema tergestinum (Grunow) Fricke 1902011101000100001B-striind-1.00o--
Gomphonema vibrio var. bohemicum (Reichelt and Fricke) R.Ross 1986100000000100000B--hbindes----
Grunowia tabellaria (Grunow) Rabenhorst 1864100010000000000B-striind-3.60a-batsme
Gyrosigma acuminatum (Kützing) Rabenhorst 1853 var. acuminatum110010000100000Btempst-strialf-----
Gyrosigma acuminatum var. gallicum (Grunow) Cleve 1894011000001000110B-st-strhlalf-----
Gyrosigma acuminatum var. lacustre (W.Smith) F.Meister 1912010000000100000B--iind--aatse
Gyrosigma attenuatum (Kützing) Rabenhorst 1853010000000100000P-Btempst-strialf-----
Gyrosigma eximium (Thwaites) Boyer 1927010000001000000B--hlalb-----
Gyrosigma kuetzingii (Grunow) Cleve 1894011000000000010----------
Gyrosigma peisonis (Grunow) Hustedt 1930011100000000001B-st-strmhalfsp2.00batee
Gyrosigma scalproides (Rabenhorst) Cleve 1894111110000101001B-strialf-----
Halamphora acutiuscula (Kützing) Levkov 2009001000000000001P-Bwarm-mhalf-1.30o--
Halamphora coffeiformis (C.Agardh) Mereschkowsky 1903110001010100000B-st-strmhalf-----
Halamphora holsatica (Hustedt) Levkov 2009010000000000010P-B-st-strhlalf-----
Halamphora hybrida (Grunow) Levkov 2009100010000000000B--mh------
Halamphora perpusilla (Grunow) Q.M.You and Kociolek 2015100010000000000B--mhalf-1.00o--
Halamphora subcapitata (Kisselev) Levkov 2009011100000100100Btempstrhlalf-----
Halamphora transcaspica (J.B.Petersen) Q.M.You and Kociolek 2015001000000000010----------
Halamphora veneta (Kützing) Levkov 2009101000000001010Btempst-strhlalf-----
Hannaea arcus (Ehrenberg) R.M.Patrick 1966 var. arcus100000000000000Bcoolstri-es0.30xatsom
Hannaea arcus var. amphioxys (Rabenhorst) R.M.Patrick 1966110000000000000Bcoolstrialfsx0.30x--
Hantzschia amphioxys (Ehrenberg) Grunow 1880100000000000000B. aertempst-striind-3.00a-me
Hantzschia amphioxys f. capitata O.Müller 1909100000000000000B-st-strIindes1.90aateo-e
Hantzschia spectabilis (Ehrenberg) Hustedt 1959001000000000000B--hlalf-----
Hantzschia virgata var. capitellata Hustedt 1930010001000000000B--hlalf-----
Hantzschia weiprechtii Grunow 1880001000000001000B--hl------
Haslea crucigera (W.Smith) Simonsen 1974010000000000010B--mh------
Hippodonta linearis (Østrup) Lange-Bertalot, Metzeltin and Witkowski 1996010000000100000B-st-strialf--oats-
Hippodonta luneburgensis (Grunow) Lange-Bertalot, Metzeltin and A.Witkowski 1996001000000000110B-st-strhlindes2.40b-a-e
Iconella hibernica (Ehrenberg) Ruck and Nakov 2016100110010000000B-st-str-ind-----
Iconella linearis (W.Smith) Ruck and Nakov 2016011000000000001B-----0.55x-oatsom
Iconella nervosa (A.W.F.Schmidt) C.Cocquyt and R.Jahn 2017010000001000000P-B-st-striind-----
Iconella splendida (Ehrenberg) Ruck and Nakov 2016011000000001010P-B-st-strialf-----
Iconella tenera (W.Gregory) Ruck and Nakov 2016010000000000001B-strialf-1.10o--
Kurtkrammeria aequalis (W.Smith) Bahls 2015111110001001001B--hbacf-1.00o-ot
Lacustriella lacustris (W.Gregory) Lange-Bertalot and Kulikovskiy 2012001000000001000B--hbind----e
Lindavia antiqua (W.Smith) Nakov, Guillory, M.L.Julius, E.C.Theriot and A.J.Alverson 2015010000000000001P-Btemp-hbacf-1.20o--
Lindavia bodanica (Eulenstein ex Grunow) T.Nakov, Guillory, Julius, Theriot and Alverson 2015010000000000001P-st-striind---hne-
Lindavia comta (Kützing) T.Nakov et al. 2015100010000000000Ptempstialf-----
Luticola kotschyana var. robusta J.Y.Li and Y.Z.Qi001000000000010B--iacf-----
Luticola cohnii (Hilse) D.G.Mann 1990010000000100000B. aer-st-str. aerialf-----
Luticola mutica (Kützing) D.G.Mann 1990100100000000000B.Stempst-strhlind-1.90o-aatse
Mastogloia braunii Grunow 1863010000010010000P-B--mhalf-----
Melosira normanii Arnott ex Van Heurck 1882010000001000010----------
Melosira undulata (Ehrenberg) Kützing 1844001000001000100P-B--iind-2.80a-o--
Melosira varians C.Agardh 1827111100001000101P-Btempst-strhlind-2.40b-a--
Meridion circulare (Greville) C.Agardh 1831100111000000000P-Btempst-striind-----
Meridion constrictum Ralfs 1843010000000100000P-Btempst-strhbind-----
Navicula arenaria Donkin 1861001000000001010B--hl--2.40b-a--
Navicula bicapitellata Hustedt 1925110010000100000B--iacf----e
Navicula capitatoradiata H.Germain ex Gasse 1986010000001000000P-Btempst-strmhalf-----
Navicula cincta (Ehrenberg) Ralfs 1861101000000000100Btempst-strhlalf-----
Navicula crucicula var. obtusata Grunow 1880010000000000001B--mh------
Navicula cryptocephala Kützing 1844100110000001010P-Btempst-striind-2.40b-a--
Navicula exigua var. elliptica Hustedt 1927010001000000001B--i---bate-
Navicula exilis Kützing 1844010000010000000B---------
Navicula fluens Hustedt 1930010000000000010B---------
Navicula gottlandica Grunow 1880001000000001000P-B--hlalfes2.50b-aatee
Navicula gregaria Donkin 1861001000000000010P-Btempst-strialf-----
Navicula johncarteri D.M.Williams 2001001000000000010B-st-strialf-1.50o-batsom
Navicula karelica var. baicalensis Skvortzov and K.I.Meyer001100000000001----------
Navicula kolbei Meister 1932011000000000010----------
Navicula lacustris var. paulseniana (J.B.Petersen) Zabelina 1951010000000100000B--i--1.00o--
Navicula lanceolata Ehrenberg 1838 var. lanceolata010000000100000----------
Navicula lanceolata var. tenella Cleve100100000000000B--i-es2.00b-om
Navicula lanceolata var. tenuirostris Skvortzov 1937010001000000001B--ialf-1.00o--
Navicula laterostrata Hustedt 1925001000000000001P-B-strialf-1.10o--
Navicula libonensis Schoeman 1970100010000000000P-B--ialf-----
Navicula meniscus Schumann 1867010000000100000-temp-hlalf-1.40o-b--
Navicula minima Grunow 1880100110000100000P-Btempst-strhlalf-1.00ohcee
Navicula oblonga (Kützing) Kützing 1844001100000001001B-st-strialfsx1.50o-bateom
Navicula peregrina (Ehrenberg) Kützing 1844 var. peregrina100010001000000P-B--mhalf-1.00o-om
Navicula peregrina var. lanceolata Skvortzov 1929010001100000001B--ialf-----
Navicula peregrina var. minuta Skvortzov 1929010001000100000B--mh-es----
Navicula placentula f. minuta J.B.Petersen 1946010000000000010B--i------
Navicula radiosa Kützing 1844111111000001000Btempst-striindsx----
Navicula rhynchocephala Kützing 1844110100000100000Btempst-strhlalf-1.30o--
Navicula rostellata Kützing 1844011100000101011B-st-strialf-0.70o-xateot
Navicula rotaeana (Rabenhorst) Grunow 1880001000000000010P-B-stiind-----
Navicula salinicola Hustedt 1939010000000100000B--mh------
Navicula slesvicensis Grunow 1880001000000000010P-B-st-strhlalf-----
Navicula tripunctata (O.F.Müller) Bory 1822100000010000000P-Btempst-strialfes---e
Navicula viridula (Kützing) Ehrenberg 1836100110000000000B-st-strhlalf-----
Navicymbula pusilla (Grunow) Krammer 2003001000000011000B--mhalf-----
Neidium bisulcatum (Lagerstedt) Cleve 1894100000001000000B-st-striind-1.00o--
Neidium iridis (Ehrenberg) Cleve 1894100000100000000Btempst-strhbind-----
Neidium kozlowii Mereschkovsky 1906100100000000000B--iind-----
Neidium lanceolata Skvortzov 1937001000000000110----------
Neidium punctulatum Hustedt010000000000010B-----0.80x-b--
Nitzschia frustulum var. asiatica Hustedt 1922100100000000000B--hl--2.40b-a-e
Nitzschia acicularis (Kützing) W.Smith 1853011001001011100P-Btempstialfes1.40o-batsom
Nitzschia angularis W.Smith 1853001000000001001B--eh--2.00bhne-
Nitzschia angustata var. curta Grunow 1881011001001000110P-B--iind-----
Nitzschia commutata Grunow 1880100110001000000P-B-st-strmhalf-----
Nitzschia dissipata (Kützing) Rabenhorst 1860101000000011110Btempst-strialfsx1.40o-b--
Nitzschia distans W.Gregory 1857010001000000001B--eh--3.60a-b-e
Nitzschia dubia W.Smith 1853100100000000000P-Btempst-strhlalf-1.00o--
Nitzschia gracilis Hantzsch 1860 var. gracilis100100000000000P-Btempst-striind-----
Nitzschia gracilis var. minor Skabichevskij 1950010001010000000B--iind-----
Nitzschia gradifera Hustedt 1922010001010000000B--hl-es0.50x-oatsm
Nitzschia heufleriana Grunow 1862110001001100001P-B-strialf---ats-
Nitzschia holsatica Hustedt 1924010000001000000P-B--iind-----
Nitzschia inconspicua Grunow 1862100010000000000Btempst-strhlalf-----
Nitzschia incurva Grunow 1878010000000100000B--mh------
Nitzschia intermedia Hantzsch ex Cleve and Grunow 1880001000000000001P-Btemp-iind-----
Nitzschia lanceolata var. minor (Grunow) H.Peragallo and M.Peragallo 1900010000111000000B--hl------
Nitzschia lanceolata W.Smith 1853 var. lanceolata010000000100000B--hlalf-----
Nitzschia linearis W.Smith 1853100100000000000Btempst-strialf-----
Nitzschia lorenziana var. subtilis Grunow 1880011000000101000B--mh------
Nitzschia microcephala Grunow 1880110101000100000P-Btempst-strialf-----
Nitzschia palea (Kützing) W.Smith 1856 var. palea100000000100000P-Btempst-striind-2.00b--
Nitzschia palea var. capitata Wislouch and Poretsky 1924110001001000000B--iind-----
Nitzschia palea var. debilis (Kützing) Grunow 1880001000000001000Btemp-iind-----
Nitzschia paleacea (Grunow) Grunow 1881111110000011000P-Btempst-strialfes2.00bateo-e
Nitzschia pamirensis Hustedt 1922010000001000000----------
Nitzschia pusilla Grunow 1862100100001000000P-B. Stempst-strialf-1.00o--
Nitzschia recta Hantzsch ex Rabenhorst 1862101100000000101Btempst-strialf-1.00o--
Nitzschia regula Hustedt 1922011000000101010------1.40o-b--
Nitzschia scalpelliformis Grunow 1880100100000000000B--mhalf-----
Nitzschia sigma (Kützing) W.Smith 1853001000000001000Btempst-strmhalf-----
Nitzschia sigmoidea (Nitzsch) W.Smith 1853110000001000000P-B-st-strialf-----
Nitzschia sinuata (Thwaites) Grunow 1880100000010000000B-st-strialf-1.90o-aatee
Nitzschia sublinearis Hustedt 1930111111001001010P-B--ialf-----
Nitzschia subtilis (Kützing) Grunow 1880110001010100000---i------
Nitzschia telezkoensis Sheshukova 1950010000001100000----------
Nitzschia thermalis (Ehrenberg) Auerswald 1861100100000000000P-B--iindes----
Nitzschia tryblionella Hantzsch 1860100000001000000B-st-striind-----
Nitzschia tubicola Grunow 1880011000000000001Btemp-mhindes2.80a-ohcee
Nitzschia vermicularis (Kützing) Hantzsch 1860011101001001001P-Btempst-strialf-----
Nitzschia vitrea G.Norman 1861001000000000010P-Btempstmhalf-2.70a-oatse
Nupela neogracillima Kulikovskiy and Lange-Bertalot 2009011000001000010P-B--iind----ot
Odontidium anceps (Ehrenberg) Ralfs 1861111000000001000P-Bcoolst-strhbind-----
Odontidium elongatum var. actinastroides (Krieger) R.M.Patrick 1939010000000000010B-st-strhlalfsx0.40x-oatsot
Odontidium hyemale (Roth) Kützing 1844111111000011011P-Bcoolst-strhbind-----
Odontidium mesodon (Kützing) Kützing 1849111001000001010Bcoolst-strhbind-0.90x-b--
Pantocsekiella kuetzingiana (Thwaites) K.T.Kiss and E.Ács 2016101100000111000P-BtempstIind-----
Pantocsekiella ocellata (Pantocsek) K.T.Kiss and Ács 2016100100000000000P-Bcoolst-strhlalf-0.90x-b-ot
Pantocsekiella rossii (H.Håkansson) K.T.Kiss and E.Ács 2016011000011000001Ptempstialf-1.00o-ot
Paralia scabrosa (Østrup) Moiseyeva 1986001000000001000B--iind-3.00a--
Paraplaconeis placentula (Ehrenberg) Kulikovskiy and Lange-Bertalot 2012100100001000000Btempst-strialf-2.00b-ot
Peroniopsis heribaudii (J.Brun and M.Peragallo) Hustedt 1952001100000000011B--iacf-2.00b--
Pinnularia angulosa Krammer 2000001000000000001B--iind---ats-
Pinnularia bogotensis (Grunow) Cleve 1895010000000000010B--iacf-----
Pinnularia borealis Ehrenberg 1843101110000011000B. aer-st-str.aeriind-1.00o-ot
Pinnularia brauniana (Grunow) Studnicka 1888010001000100000P-B-st-striacf-----
Pinnularia brebissonii (Kützing) Rabenhorst 1864101100000011000Btempst-striind-1.00o--
Pinnularia intermedia (Lagerstedt) Cleve 1895010000001000000P-Bcoolst-striind-1.00o--
Pinnularia isostauron (Ehrenberg) Cleve 1895010000000000000B--iind--oatsom
Pinnularia karelica var. baicalensis Skvortzov and K.I.Meyer 1928010000001000000----------
Pinnularia microstauron (Ehrenberg) Cleve 1891 var. microstauron011000000100110P-Btempst-striind-0.30xatsot
Pinnularia microstauron var. diminuta Shirshov 1935100100000000000B--i--1.00o--
Pinnularia oriunda Krammer 1992001000000001000B--ineu-1.00oatsot
Pinnularia paragracillima Kulikovskiy, Lange-Bertalot and Witkowski 2010010000000000001B-striind-1.00o-om
Pinnularia pectinalis var. rostrata Skvortzov 1937010000000000000----------
Pinnularia subborealis Hustedt 1922100100000000000B--i--0.20xatsot
Pinnularia subcapitata W.Gregory 1856010000010000000Btempst-striacf-0.60o-x--
Pinnularia sudetica Hilse 1861001000000001110B--hbneu-1.00o--
Placoneis exigua (W.Gregory) Mereschkovsky 1903110111000000000B-striindes1.40o-b--
Placoneis dicephala (Ehrenberg) Mereschkowsky 1903100110000000000B--iindes2.00bateme
Placoneis elginensis (W.Gregory) E.J.Cox 1988100010000000000P-B-st-strialf-----
Placoneis placentula var. lanceolata (Grunow) Aboal 2003100000001000000B--ialf-----
Planothidium grimmei (Krasske) I.W.Bishop and Spaulding 2018100000010000000B-----1.00oatsom
Planothidium lanceolatum (Brébisson ex Kützing) Lange-Bertalot 1999110111001000000Bwarm-ialfsx1.60b-oatee
Planothidium rostratoholarcticum Lange-Bertalot and Bak 2015100000000000000B-st-strialf-1.60b-o-om
Pleurosira laevis (Ehrenberg) Compère 1982001000000011000P-Beterm-ehalf-----
Prestauroneis protracta (Grunow) Kulikovskiy and Glushchenko 2016001000000000001P-B-st-strmhind-0.40x-oatee
Psammothidium marginulatum (Grunow) Bukhtiyarova and Round 1996001000000000001Btempst-strhbacfsx0.20xatsot
Pseudostaurosira brevistriata var. capitata (Héribaud) N.A.Andresen. Stoermer. and R.G.Kreis. Jr. 2000100010000000000P-B--ialfes1.20oatso-e
Rhoicosphenia abbreviata (C.Agardh) Lange-Bertalot 1980101100000001100Btempst-strialfes1.90o-aateme
Rhopalodia gibba (Ehrenberg) O.Müller 1895 var. gibba110000010000000P-Btempst-strialfes1.40x-oateom
Rhopalodia gibba var. mongolica (Østrup) Proshkina-Lavrenko 1950010000010000010----------
Rhopalodia gibberula var. producta (Grunow) O.Müller 1900010000010000000B-strhlalf-----
Sellaphora americana (Ehrenberg) D.G.Mann 1989001000000000010B-strialf-1.50o-batsot
Sellaphora bacillum (Ehrenberg) D.G.Mann 2018001000000000001B-st-strialfsx1.50o-batsme
Sellaphora hustedtii (Krasske) Lange-Bertalot and Werum 2004100110000000000B-striindsx0.30x--
Sellaphora lambda (Cleve) Metzeltin and Lange-Bertalot 1998001000000001000B--i------
Sellaphora mutata (Krasske) Lange-Bertalot 1996001100000000001B-st-strhlindes1.90bhneom
Sellaphora parapupula Lange-Bertalot 1996010000001000000B-stiind-1.00oatem
Sellaphora pupula (Kützing) Mereschkovsky 1902001000000000010Betermst-strhlindsx1.90o-aateme
Sellaphora rostrata (Hustedt) J.R.Johansen 2004001000000000001Btemp-hlind-1.90o-ahne-
Sellaphora seminulum (Grunow) D.G.Mann 1989110000011000000P-Btempst-striindsp2.50b-ahnee
Sellaphora verecunda (Hustedt) C.E.Wetzel, L.Ector, B.Van de Vijver, Compère and D.G.Mann 2015010000001000000----------
Sellaphora wummensis J.R.Johansen 2004101100000000010B--hlindes1.90o-ahneme
Stauroneis anceps Ehrenberg 1843111100000110110P-Btempst-striindsx1.30oatsom
Stauroneis parvula (Grunow) Cleve. nom. illeg. 1894011000000101010B-stmhind-----
Stauroneis smithii Grunow 1860 var. smithii100000010000000P-B-st-strialf-1.00o-om
Stauroneis smithii var. karelica Wislouch and Kolbe 1917001000000000110Bcool-i--1.00o-ot
Staurophora wislouchii (Poretzsky and Anisimova) D.G.Mann 1990010000000100000B--mh------
Staurosira construens var. triundulata (Reichelt) Bukhtiyarova 1995100000100000000P-Btempst-strialf-1.00o--
Staurosira dubia Grunow. nom. inval. 1879100000010000000P--ialfsp1.30oateme
Staurosira leptostauron (Ehrenberg) Kulikovskiy and Genkal 2011100000000100000P-Btempst-strialf-1.30o--
Staurosira subsalina (Hustedt) Lange-Bertalot 2004111110000001000P-B-st-strhlalf-----
Staurosira venter (Ehrenberg) Cleve and J.D.Möller 1879100110000000000P-Btempst-strialf-1.30o-ot
Staurosirella martyi (Héribaud) Morales and Manoylov 2006001100000000001B----es2.70a-o--
Staurosirella pinnata (Ehrenberg) D.M.Williams and Round 1988100000011000000P-Btempst-strhlalfes1.10oatsom
Staurosirella rhomboides (Grunow) E.A.Morales and K.M.Manoylov 2010100110000000000B-sthbalf-1.00o--
Stenopterobia intermedia (F.W.Lewis) Van Heurck ex Hanna 1933001000000000110B--hbacf-1.00o-ot
Stephanodiscus minutulus (Kützing) Cleve and Möller 1882010001000000001Ptemp-ialb-----
Surirella conifera var. punctata Skvortsov010000000100000----------
Surirella angusta Kützing 1844101110000100000B--iind-----
Surirella capronii var. hankensis Skvortzov 1929010000011000001----------
Surirella didyma var. minor Skvortzov 1937001000000000010B--ialf-----
Surirella grunowii Kulikovskiy, Lange-Bertalot and Witkovski 2010001000000000001B--iind-----
Surirella librile (Ehrenberg) Ehrenberg 1845110110110100000P-Btempst-strialf---hne-
Surirella minuta Brébisson ex Kützing. nom. illeg. 1849110100001000000Btempst-strialf-----
Surirella ovalis Brébisson 1838101100000001000P-B-st-strmhalfes1.70b-o--
Surirella quadricornis Jasnitsky 1936010000000100000----------
Surirella salina W.Smith 1851001000000000110B-st-striindes1.20oatsot
Surirella turgida var. skvortzowii (K.I.Meyer) Kisselev 1950001000000000001----------
Synedra famelica Kützing 1844101000010001000P-B-strialf-1.50o-b-ot
Synedra goulardii Brébisson ex Cleve and Grunow 1880 var. goulardii100110000100000P-B--iind-----
Synedra goulardii var. telezkoensis Poretzky ex Proshkina-Lavrenko 1950100000100000000-----es----
Synedra actinastroides (Lemmermann) Lemmermann 1900010000000100000----------
Tabellaria fenestrata (Lyngbye) Kützing 1844011001000001100P-B-st-striind-1.90o-a--
Tabellaria flocculosa (Roth) Kützing 1844011000001101010P-Betermst-striacf-3.00a--
Tabularia parva (Kützing) D.M.Williams and Round 1986100000000000000---mhalf-----
Tabularia tabulata (C.Agardh) Snoeijs 1992101010000011001B--mhalf-----
Tryblionella angustata W.Smith 1853100100000000000P-Btempstialfsx1.50o-batse
Tryblionella apiculata W.Gregory 1857100000000100000B-st-strmhalfes2.70a-oatee
Tryblionella debilis Arnott ex O’Meara 1873001000000011000P-Btempst-str. aerialfes2.60a-oatee
Tryblionella hungarica (Grunow) Frenguelli 1942100110001000000P-B-st-strmhalfsp2.90aatee
Tryblionella levidensis W.Smith 1856010000010000000P-B-st-strhlalfsp2.60a-oatee
Tryblionella victoriae Grunow 1862010000000100000B-st-strhlalfsp2.60a-oatee
Ulnaria oxyrhynchus (Kützing) Aboal 2003010000001100001P-B-st-strialfes2.40b-aatse
Ulnaria ulna (Nitzsch) Compère 2001 var. ulna111110110010000P-Btempst-strialfes2.40b-aatee
Ulnaria aequalis (Kützing) D.M.Williams and Van de Vijver 2021111100001000000P-B--ialfsp2.00b-om
Ulnaria amphirhynchus (Ehrenberg) Compère and Bukhtiyarova 2006110100000100000P-B--ialfes2.00bhneom
Ulnaria capitata (Ehrenberg) Compère 2001100100000000000P-B-st-strialfes2.00batse
Ulnaria danica (Kützing) Compère and Bukhtiyarova 2006100110001000000P-Btemp-ialfes1.70b-ohneom
Ulnaria delicatissima var. angustissima (Grunow) Aboal and P.C.Silva 2004001000000000010P-B--ialfes1.70b-o-om
Ulnaria ulna var. spathulifera (Grunow) Aboal 2003001000000001110B-st-strialf-1.70b-oatse
Note: Upper—St. 1, 2; Middle—St 3, 4, 5, 6; Lower—St. 7, 8, 9, 10, 11, 12. Abbreviation for ecological groups: Habitat preferences (Hab): B, benthic; P-B, planktonic-benthic; P, planktonic. Water temperature (T): cool, cool-loving species; temp, temperate temperature water inhabitants; eterm, eurythermic species; warm, warm water inhabitants. Streaming and Oxygenation (OXY): aer, aerophiles; str, streaming waters inhabitant; st-str, low streaming waters inhabitant; st, standing water inhabitant. Water pH (pH): acf, acidophilic species; ind, indifferent; alf, alkaliphilic species; alb, alkalibiontes. Water salinity (HAL): hb, halophobe; i, oligohalobious-indifferent; hl, oligohalobious-halophilous; mh, mesohalobious. Organic pollution, Watanabe (D): sx, saproxenes; es, eurysaprobes; sp, saprophiles. Organic pollution and self-purification zones by Sládeček (SAP): indicators of Class of Water Quality I: x—0.0—xenosaprobiont; x-o—0.4—xeno-oligosaprobiont; Class of Water Quality II: o-x—0.6—oligo-xenosaprobiont; x-b—0.8—xeno-beta-mesosaprobiont; o—1.0—oligosaprobiont; o-b—1.4—oligo-beta-mesosaprobiont; Class of Water Quality III: b-o—1.6—beta-oligosaprobiont; o-a—1.8—oligo-alpha-mesosaprobiont; b—2.0—beta-mesosaprobiont; b-a—2.4—beta-alpha-mesosaprobiont; Class of Water Quality IV: a-o—2.6—alpha-oligosaprobiont; a—3.0 –alpha-mesosaprobiont; Class of Water Quality V: a-b—3.6—alpha-beta-mesosaprobiont. Index saprobity s (S): species-specific index saprobity according Sládeček. Trophic state (TRO): ot, oligotraphentic; o-m, oligo-mesotraphentic; m, mesotraphentic; me, meso-eutraphentic; e, eutraphentic; o-e, oligo- to eutraphentic. Nutrition type as Nitrogen uptake metabolism (AUT-HET): ats, nitrogen-autotrophic taxa, tolerating very small concentrations of organically bound nitrogen; ate, nitrogen-autotrophic taxa, tolerating elevated concentrations of organically bound nitrogen; hne, facultatively nitrogen-heterotrophic taxa, needing periodically elevated concentrations of organically bound nitrogen; hce, nitrogen-heterotrophic taxa, needing elevated concentrations of organically bound nitrogen.
Table A3. Diatom indicator species distribution over the sampling stations of the Zarafshan River.
Table A3. Diatom indicator species distribution over the sampling stations of the Zarafshan River.
VariableSt.1St.2St.3St.4St.5St.6St.7St.8St.9St.10St.11St.12
Habitat
B5938237402644843225264
P-B43281351831271330112618
P121032134075
Temperature
cool312001114242
temp4829981720271227162126
eterm010001213130
warm111011100011
Oxygen
aer000011100000
str6540318151311
st-str55301382928391340224028
st871055335187
Salinity
eh012000212014
mh1092046959498
hl1773299111971310
i65422594037471648185151
hb554133618479
pH
acb110010100000
acf431022502269
ind3018144161724728153325
alf57361463130321538153335
alb121011211012
Watanabe
sx1154154548389
es22134277115139810
sp510053301112
Autotrophy-Heterotrophy
ats96711111133961314
ate201231125116115914
hne730143224147
hce110001101001
Trophy
ot106209861961315
om104417107372810
m211022201013
me761143113143
e1892195123861211
o-e130000122000
he000010000000
Class of Water Quality
Class 1411042521143
Class 2342483211722726132238
Class 33013641021051361615
Class 4411034326363
Class 5011000000001
Note: Abbreviation for ecological groups: Habitat preferences (Hab): B, benthic; P-B, planktonic-benthic; P, planktonic. Water temperature (T): cool, cool-loving species; temp, temperate temperature water inhabitants; eterm, eurythermic species; warm, warm water inhabitants. Streaming and Oxygenation (OXY): aer, aerophiles; str, streaming waters inhabitant; st-str, low streaming waters inhabitant; st, standing water inhabitant. Water pH (pH): acf, acidophilic species; ind, indifferent; alf, alkaliphilic species; alb, alkalibiontes. Water salinity (HAL): hb, halophobe; i, oligohalobious-indifferent; hl, oligohalobious-halophilous; mh, mesohalobious. Organic pollution, Watanabe (D): sx, saproxenes; es, eurysaprobes; sp, saprophiles. Index saprobity s (S): species-specific index saprobity according Sládeček. Trophic state (TRO): ot, oligotraphentic; o-m, oligo-mesotraphentic; m, mesotraphentic; me, meso-eutraphentic; e, eutraphentic; o-e, oligo- to eutraphentic. Nutrition type as Nitrogen uptake metabolism (AUT-HET): ats, nitrogen-autotrophic taxa, tolerating very small concentrations of organically bound nitrogen; ate, nitrogen-autotrophic taxa, tolerating elevated concentrations of organically bound nitrogen; hne, facultatively nitrogen-heterotrophic taxa, needing periodically elevated concentrations of organically bound nitrogen; hce, nitrogen-heterotrophic taxa, needing elevated concentrations of organically bound nitrogen.

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Figure 1. Sampling stations over the Zarafshan River; numbers are described in Table 1.
Figure 1. Sampling stations over the Zarafshan River; numbers are described in Table 1.
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Figure 2. Comparative heat map of chemical variable distribution over sampling stations in the Zarafshan River, Abbreviations in the y-axis and station numbers in the x-axis are the same as in Table 1. The color of the cells changes from blue to red depending on the magnitude of the value of each variable in the amplitude of the values of all variables.
Figure 2. Comparative heat map of chemical variable distribution over sampling stations in the Zarafshan River, Abbreviations in the y-axis and station numbers in the x-axis are the same as in Table 1. The color of the cells changes from blue to red depending on the magnitude of the value of each variable in the amplitude of the values of all variables.
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Figure 3. Distribution of critical chemical variables over sampling stations in the Zarafshan River.
Figure 3. Distribution of critical chemical variables over sampling stations in the Zarafshan River.
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Figure 4. Distribution of biological variables: species number, sum of scores, and Index saprobity, S, over sampling stations in the Zarafshan River. Poly. Is the polynomial trend line.
Figure 4. Distribution of biological variables: species number, sum of scores, and Index saprobity, S, over sampling stations in the Zarafshan River. Poly. Is the polynomial trend line.
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Figure 5. Distribution of bioindicators over the upper, middle, and lower parts of the Zarafshan River. Abbreviation for ecological groups: Substrate preferences (a): B, benthic; P-B, planktonic-benthic; P, planktonic. Water temperature (b): cool, cool-loving species; temp, temperate temperature water inhabitants; eterm, eurythermic species; warm, warm water inhabitants. Water pH (c): acb, acidobiontic species; acf, acidophilic species; ind, indifferent species; alf, alkaliphilic species; alb, alkalibiontic species. Oxygen (d): aer, aerophiles; str, streaming waters inhabitant; st-str, low streaming waters inhabitant; st, standing water inhabitant. Water salinity (e): hb, halophobe; i, oligohalobious-indifferent; hl, oligohalobious-halophilous; mh, mesohalobious; eh, euhalobous. Organic pollution, Watanabe (f): sx, saproxenes; es, eurysaprobes; sp, saprophiles. Autotrophy-Heterotrophy, Nutrition type as Nitrogen uptake metabolism (g): ats, nitrogen-autotrophic taxa, tolerating very small concentrations of organically bound nitrogen; ate, nitrogen-autotrophic taxa, tolerating elevated concentrations of organically bound nitrogen; hne, facultatively nitrogen-heterotrophic taxa, needing periodically elevated concentrations of organically bound nitrogen; hce, nitrogen-heterotrophic taxa, needing elevated concentrations of organically bound nitrogen. Trophic state (h): ot, oligotrafentic; o-m, oligo-mesotraphentic; m, mesotraphentic; me, meso-eutraphentic; e, eutraphentic; o-e, oligo- to eutraphentic; he, hypereutraphentic. Water quality class of organic pollution according to species-specific index saprobity S of Sládeček (i).
Figure 5. Distribution of bioindicators over the upper, middle, and lower parts of the Zarafshan River. Abbreviation for ecological groups: Substrate preferences (a): B, benthic; P-B, planktonic-benthic; P, planktonic. Water temperature (b): cool, cool-loving species; temp, temperate temperature water inhabitants; eterm, eurythermic species; warm, warm water inhabitants. Water pH (c): acb, acidobiontic species; acf, acidophilic species; ind, indifferent species; alf, alkaliphilic species; alb, alkalibiontic species. Oxygen (d): aer, aerophiles; str, streaming waters inhabitant; st-str, low streaming waters inhabitant; st, standing water inhabitant. Water salinity (e): hb, halophobe; i, oligohalobious-indifferent; hl, oligohalobious-halophilous; mh, mesohalobious; eh, euhalobous. Organic pollution, Watanabe (f): sx, saproxenes; es, eurysaprobes; sp, saprophiles. Autotrophy-Heterotrophy, Nutrition type as Nitrogen uptake metabolism (g): ats, nitrogen-autotrophic taxa, tolerating very small concentrations of organically bound nitrogen; ate, nitrogen-autotrophic taxa, tolerating elevated concentrations of organically bound nitrogen; hne, facultatively nitrogen-heterotrophic taxa, needing periodically elevated concentrations of organically bound nitrogen; hce, nitrogen-heterotrophic taxa, needing elevated concentrations of organically bound nitrogen. Trophic state (h): ot, oligotrafentic; o-m, oligo-mesotraphentic; m, mesotraphentic; me, meso-eutraphentic; e, eutraphentic; o-e, oligo- to eutraphentic; he, hypereutraphentic. Water quality class of organic pollution according to species-specific index saprobity S of Sládeček (i).
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Figure 6. Bray–Curtis tree of similarity for chemical variables in sampling stations 2–9 of the Zarafshan River.
Figure 6. Bray–Curtis tree of similarity for chemical variables in sampling stations 2–9 of the Zarafshan River.
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Figure 7. Bray–Curtis tree of similarity for chemical variables and bioindicators in sampling stations 2–9 of the Zarafshan River.
Figure 7. Bray–Curtis tree of similarity for chemical variables and bioindicators in sampling stations 2–9 of the Zarafshan River.
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Figure 8. Bray–Curtis similarity tree of bioindicators in sampling stations 2–9 of the Zarafshan River.
Figure 8. Bray–Curtis similarity tree of bioindicators in sampling stations 2–9 of the Zarafshan River.
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Figure 9. JASP Network plot of correlation on the level greater than 50% for chemical and bioindicator variable values for seven stations (St.) of the Zarafshan River. The line thickness between stations reflects the correlation value (only significant results are represented); blue is positive, red is negative. Clusters 1 and 2 are outlined by color dashed lines.
Figure 9. JASP Network plot of correlation on the level greater than 50% for chemical and bioindicator variable values for seven stations (St.) of the Zarafshan River. The line thickness between stations reflects the correlation value (only significant results are represented); blue is positive, red is negative. Clusters 1 and 2 are outlined by color dashed lines.
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Figure 10. JASP Network plot of correlation on the level greater than 50% for bioindicator variable values only for twelve stations (St.) of the Zarafshan River. The line thickness between stations reflects the correlation value (only significant results are represented); blue is positive, red is negative. Clusters 1 and 2 are outlined by color dashed lines.
Figure 10. JASP Network plot of correlation on the level greater than 50% for bioindicator variable values only for twelve stations (St.) of the Zarafshan River. The line thickness between stations reflects the correlation value (only significant results are represented); blue is positive, red is negative. Clusters 1 and 2 are outlined by color dashed lines.
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Figure 11. Index toxicity (WESI) distribution over sampling stations 2–9 in the Zarafshan River. The dynamics of the WESI values can be traced along the entire river through the southern branch cross station 5 with the orange color and through the northern branch cross station 6 with the blue color.
Figure 11. Index toxicity (WESI) distribution over sampling stations 2–9 in the Zarafshan River. The dynamics of the WESI values can be traced along the entire river through the southern branch cross station 5 with the orange color and through the northern branch cross station 6 with the blue color.
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Figure 12. Distribution of Water Quality Class in organic pollution (a) and Index WESI (b) over sampling stations and catchment basin areas in the Zarafshan River.
Figure 12. Distribution of Water Quality Class in organic pollution (a) and Index WESI (b) over sampling stations and catchment basin areas in the Zarafshan River.
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Table 1. Sampling sites, river part, code, coordinates, altitude, and distance from the Tajikistan border of the Zarafshan River.
Table 1. Sampling sites, river part, code, coordinates, altitude, and distance from the Tajikistan border of the Zarafshan River.
SiteNo.River PartCodeNorthEastAltitude, m a.s.l.Distance, km
Fandarya1UpperFan39°23′2.91″68°38′32.02″14550
Upper Zeravschan2UpperUp-Zer39°25′1.48″68°30′56.40″140321
Pervomayskaya plotina3MiddleP-mays39°32′16.87″67°24′36.43″880188
Upper Choponata4MiddleUp-Chop39°41′40.29″67° 3′14.25″70238
Akdarya5MiddleAkda39°53′20.18″66°28′30.56″52262
Karadarya6MiddleKara39°58′26.02″66°33′46.88″52355.5
Khatirchi7LowerKhat40°0′47.40″65°56′34.06″42752.3
Pakhtakor8LowerPakh40°1′59.89″65°45′42.50″39632.11
Navoi9LowerNavo40°9′32.56″65°19′47.08″33034.35
Gizhduvon10LowerGizh40°3′48.40″64°46′26.15″27754.74
Bukhara11LowerBukh39°49′57.97″64°19′38.60″21448.47
Karakul12LowerKara39°29′53.98″63°49′58.58″19763.12
Table 2. River pollution index (RPI) for environmental and biological variables crosses two different channels of the Zarafshan River.
Table 2. River pollution index (RPI) for environmental and biological variables crosses two different channels of the Zarafshan River.
VariableRPI Cross 5 AverageRPI Cross 6 Average
km479.7469.1
O2 mg L−17.407.77
BOD, mgO L−11.101.11
COD, mgO L−17.548.01
N-NH4, mg L−10.050.06
N-NO2, mg L−10.550.90
N-NO3, mg L−10.950.96
Fe, mg L−10.020.02
Cu, mcg L−12.843.30
Zn, mcg L−12.963.29
Phenols, mg L−10.0020.003
Oil, mg L−10.010.02
Detergents, mg L−10.000.01
TSS, mg L−1380.3507.0
DDT, mg L−10.00.0
Alpha-HCH, mcg L−10.00040.0004
Gamma-HCH, mcg L−10.00.0
Cr VI, mcg L−10.480.46
F, mg L−10.330.36
As, mcg L−10.921.09
TDS, mg L−1505.7545.8
No of Species58.4858.65
Sum of scores154.03155.07
Index S1.531.56
Note: Maximal critical values of RPI are given in bold.
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Mamanazarova, K.; Alimjanova, K.; Barinova, S. Biodiversity of Diatoms as Indicators of Water Quality and Landscape Sustainable Dynamics in the Zarafshan River, Uzbekistan. Land 2024, 13, 1809. https://doi.org/10.3390/land13111809

AMA Style

Mamanazarova K, Alimjanova K, Barinova S. Biodiversity of Diatoms as Indicators of Water Quality and Landscape Sustainable Dynamics in the Zarafshan River, Uzbekistan. Land. 2024; 13(11):1809. https://doi.org/10.3390/land13111809

Chicago/Turabian Style

Mamanazarova, Karomat, Kholiskhon Alimjanova, and Sophia Barinova. 2024. "Biodiversity of Diatoms as Indicators of Water Quality and Landscape Sustainable Dynamics in the Zarafshan River, Uzbekistan" Land 13, no. 11: 1809. https://doi.org/10.3390/land13111809

APA Style

Mamanazarova, K., Alimjanova, K., & Barinova, S. (2024). Biodiversity of Diatoms as Indicators of Water Quality and Landscape Sustainable Dynamics in the Zarafshan River, Uzbekistan. Land, 13(11), 1809. https://doi.org/10.3390/land13111809

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